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inverse problems. The team aims at developing Bayesian computational methods for such (ill-posed) inverse problems and aims both at increasing their validity and at reducing their computational cost. In
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, Ultrasound and Vibration, Aircraft Structures, Damage Assessment, Structural Health Monitoring, Structural Health Prognosis, Bayesian Statistics, Machine Learning Informal enquiries prior to making
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, protein biochemistry, electron and fluorescence microscopy and CRISPR/Cas9 genome editing to study the role of the early autophagy machinery in targeting and degrading protein aggregates and organelles
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in more detail for targeted treatment adaptations. Key challenges to disentangle risk factors for neurocognitive impairment in patients include tumour size, location, treatment specifics, age, sex, and
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positioning), and its implementation in 5G cellular infrastructure. Extraction of analytics from multiple target users. DC12: Geo-statistical analysis of spectrum data for coverage/performance maps Host